Expert finding systems allow users to type simple text queries and retrieve names of individuals who possess the expertise described in the queries. Such applications are especially useful in real world: conference orga- nizers may search for reviewers, company recruiters may search for talented candidates, graduate students may search for advisers and researchers may search for collaborators, etc. In this study, we propose Hefbib, a hierarchical approach to expert finding in heterogeneous bibliographic network, to construct an expert hierarchy given a seed textual topic hierarchy as well as retrieve authoritative experts given a search query. Experiments on synthetic toy examples and real-world DBLP dataset show promising results.